In our manuscript, we utilized scRNA-seq libraries we generated (Classification of human chronic inflammatory skin disease based on single-cell immune profiling (science.org)), samples from the Reynolds et al dataset ( Developmental cell programs are co-opted in inflammatory skin disease (science.org)), and samples from the Bangert et al dataset (Persistence of mature dendritic cells, TH2A, and Tc2 cells characterize clinically resolved atopic dermatitis under IL-4Rα blockade (science.org)). An integrated object encompassing samples from these three datasets (Three_together.rds) was generated utilizing the following steps (see the code at Yale73/scRNA-seq-for-diverse-human-rashes (github.com)). 1. We first performed QC, normalized, and integrated our generated scRNA-seq data to make an initial Seurat object. (See "Initial low resolution integration-FigureS1A.Rmd"). A Seurat object containing this manuscript data is provided below (Manuscript_raw.rds). 2. The Reynolds et al dataset is from Zenodo DOI: 10.5281/zenodo.4249674. Their object was transferred into a Seurat object and then log-transformed and scaled by RStudio. Then immune cell clusters were subsetted based on the "final_clustering" in the object. 3. The Bangert et al dataset was obtained via the GEO repository (identifiers GSE153760 and GSE158432) and a Seurat object was created by performing QC, normalization, and integration. (See code:https://github.com/Yale73/scRNA-seq-for-diverse-human-rashes/blob/main/Made%20the%20final%2041-cluster%20object/SI_Banget_integration.R) 4. Before integrating the three above objects, we labeled the 10X Genomics scRNA-seq kit type/chemistry, the 10X Genomics CellRanger version, as well as the data source, to utilize in batch correction. 5. The three objects were then integrated with harmony batch correction for the individual samples, kit chemistry, the CellRanger version, as well as the data source (https://github.com/Yale73/scRNA-seq-for-diverse-human-rashes/blob/main/Made%20the%20final%2041-cluster%20object/Mix%203%20datasets.R). 6. After integration, we removed contaminant non-immune cells or dying cells to generate the final object (Three_together.rds), as well as subsetted versions of this final object for each of the original three datasets (Manuscript_Object.rds, S_Reynolds.rds, and SI_Bangert.rds)